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svm algorithm  (MathWorks Inc)


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    MathWorks Inc svm algorithm
    Svm Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/svm+algorithm/pm40189123-138-1-16
    Average 90 stars, based on 1 article reviews
    svm algorithm - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Chromatin compaction during confined cell migration induces and reshapes nuclear condensates
    Article Snippet: Phase boundary is determined using an unbiased automated SVM algorithm in MATLAB using polynomial fit as detailed previously .

    Article Title: Rock mass classification prediction model using heuristic algorithms and support vector machines: a case study of Chambishi copper mine
    Article Snippet: The model is built and trained using the MATLAB software and the main part is based on the SVM algorithm using the LIBSVM toolbox , .

    Article Title: Multiplexed in-Series Macro-Bend Fiber Sensors for Personal Authentication Through Foot Recognition
    Article Snippet: The 2-dimensional dataset resulting from PCA (60 data points in the graph of Fig. 4(b)) was used as an input for an SVM algorithm performed in Matlab, which resulted in an accuracy of 85.2% for testing data.

    Article Title: Automated transtibial prosthesis alignment: A systematic review.
    Article Snippet: This comprehensive systematic review critically analyzes the current progress and challenges in automating transtibial prosthesis alignment.. The manual identification of alignment changes in prostheses has been found to lack reliability, necessitating the development of automated processes.. Through a rigorous systematic search across major electronic databases, this review includes the highly relevant studies out of an initial pool of 2111 records.

    Article Title: Theta-gamma phase-amplitude coupling as a promising neurophysiological biomarker for evaluating the efficacy of low-intensity focused ultrasound stimulation on vascular dementia treatment.
    Article Snippet: Low-intensity focused ultrasound stimulation (LIFUS) has garnered attention for its potential in vascular dementia (VD) treatment.. However, the lack of sufficient data supporting its efficacy and elucidating its mechanisms of action limits its further clinical translation and application.. Considerable researches support the idea that LIFUS can improve the disturbance of neural oscillation modes caused by a variety of neurological diseases.

    Article Title: AI-Based Soft Module for Safe Human-Robot Interaction towards 4D Printing.
    Article Snippet: Sufficient training and testing data were used for classification via the SVM algorithm in the machine learning package in MATLAB.

    Article Title: Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis
    Article Snippet: For the SVM algorithm, we used the built-in function in MATLAB, using the default linear kernel for binary classification.

    Article Title: Emotion Recognition from Physiological Signals Collected with a Wrist Device and Emotional Recall.
    Article Snippet: For classification and hyperparameter optimization, we implemented an SVM algorithm in Matlab.



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    Effect of class weight tuning on SVM decision boundaries for the Telco 1 dataset based on F1-score metric.

    Journal: PeerJ Computer Science

    Article Title: Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning

    doi: 10.7717/peerj-cs.2949

    Figure Lengend Snippet: Effect of class weight tuning on SVM decision boundaries for the Telco 1 dataset based on F1-score metric.

    Article Snippet: Interestingly, the SVM algorithm performed well on both the Telco 3 and insurance datasets, particularly with moon-shaped clusters as shown in and .

    Techniques:

    Effect of class weight tuning on SVM decision boundaries for the Telco 3 dataset based on F1-score metric.

    Journal: PeerJ Computer Science

    Article Title: Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning

    doi: 10.7717/peerj-cs.2949

    Figure Lengend Snippet: Effect of class weight tuning on SVM decision boundaries for the Telco 3 dataset based on F1-score metric.

    Article Snippet: Interestingly, the SVM algorithm performed well on both the Telco 3 and insurance datasets, particularly with moon-shaped clusters as shown in and .

    Techniques: